Method for supporting a camera-based environment recognition by a means of transport using road wetness information from a first ultrasonic sensor

ABSTRACT

A method and an apparatus for supporting a camera-based environment recognition by a means of transport using road wetness information from a first ultrasonic sensor. The method includes: recording a first signal representing an environment of the means of transport by the first ultrasonic sensor of the means of transport; recording a second signal representing the environment of the means of transport by a camera of the means of transport; obtaining road wetness information on the basis of the first signal; selecting a predefined set of parameters from a plurality of predefined sets of parameters as a function of the road wetness information; and performing an environment recognition on the basis of the second signal in conjunction with the predefined set of parameters.

FIELD

The present invention relates to a method for supporting a camera-basedenvironment recognition by a means of transport using road wetnessinformation from a first ultrasonic sensor.

BACKGROUND INFORMATION

In the related art, conventional means of transport perform acamera-based environment recognition to obtain information about objectsin the environment of the means of transport. This information isreceived, for example, by driver assistance systems and/or systems forautonomously controlling the means of transport and used by the same.Such an environment recognition is based on conventional image analysisalgorithms and object classification algorithms that generally use oneor more classifiers for certain objects.

Also conventional are rain sensors for means of transport for sensingthe presence of a precipitation. They are usually mounted in an upperarea of a windshield of the means of transport and are adapted forsensing the presence of precipitation on the windshield. Wetnessinformation ascertained by such a rain sensor can be used to selectsuitable classifiers of an environment recognition.

Also conventional are ultrasonic sensors which are often used inconnection with means of transport for parking assistance systems orsimilar driver assistance systems. To be able to ascertain distances ofobjects in the environment of the means of transport to the means oftransport on the basis of propagation times of the ultrasonic signals,such ultrasonic sensors are mostly mounted for this purpose on means oftransport in such a way that the emission and sensing direction thereofare essentially horizontal to the means of transport.

SUMMARY

In accordance with a first aspect of the present invention, a method isprovided for supporting a camera-based environment recognition by ameans of transport using road wetness information from a firstultrasonic sensor. The means of transport (i.e., transport device) maybe a road vehicle (for example, a motorcycle, passenger vehicle,transport vehicle, truck) or a rail vehicle or an aircraft/airplane or awatercraft, for example. Moreover, the method steps described in thefollowing may be performed completely or partially by an apparatus ofthe means of transport, in accordance with the present invention. Theapparatus may include an evaluation unit which preferably has a datainput. The evaluation unit may be in the form of an ASIC, FPGA,processor, digital signal processor, microcontroller, or the like and beconnected by information technology to an internal and/or externalmemory unit. Moreover, the evaluation unit may be adapted to implementthe method according to the present invention in conjunction with acomputer program executed by the evaluation unit.

In a first step of the method according to an example embodiment of thepresent invention, a first signal representing an environment of themeans of transport is recorded by the first ultrasonic sensor of themeans of transport. The ultrasonic sensor may also be an ultrasonicsensor of the means of transport that is/may be used for other purposes.Alternatively or additionally, a dedicated ultrasonic sensor may also beused for the method according to the example embodiment of the presentinvention. The ultrasonic sensor of the means of transport may be anultrasonic sensor of a parking assistance system or of another driverassistance system of the means of transport, for example. The ultrasonicsensor may be mounted in a front bumper or in the area of a rear-endsection of the means of transport or also at other positions of themeans of transport, for example, making it possible for both the tirenoises, as well as the roadway ahead or behind and the environmentthereof to be recorded. Moreover, the ultrasonic sensor may be directlyor indirectly connected by information technology (i.e., for example,via another control unit of the means of transport) to the data input ofthe evaluation unit according to the present invention. The connectionmay be established, for example, via a bus system (for example, CAN,LIN, MOST, Ethernet, etc.) of an electrical system of the means oftransport. The first signal of the first ultrasonic sensor received bythe evaluation unit may be initially stored in the memory unit connectedto the evaluation unit for a subsequent processing by the evaluationunit.

In a second step of the method according to the present invention, asecond signal representing the environment of the means of transport isrecorded by a camera of the means of transport. The second signal maypreferably be acquired at an instant that is essentially identical tothat of the first signal, making it possible to ensure that the twosignals each contain temporally corresponding environment information. Atime offset between the two signals may arise due to different sensortypes and different signal processing chains and signal transmissionchains. A time offset between the two signals may be within a range thatis preferred, but not necessarily to be ensured for the example method,for example, of between a few milliseconds and a few hundredmilliseconds, or also in the second range. The camera may be a 2D or 3Dcamera having a standard image resolution, an HD or an ultra-HD imageresolution, or an infrared camera, for example. The camera maypreferably be mounted and oriented on the means of transport in a waythat enables it to capture an environment ahead of the same. However,such a placement and/or orientation of the camera is not limited to thisexample. Analogously to the first ultrasonic sensor, the camera may bedirectly or indirectly connected by information technology to theevaluation unit according to the present invention via the electricalsystem of the means of transport. A preferred specific embodiment of thepresent invention provides that the camera be connected by informationtechnology to an image processing unit of the means of transport that isadapted for receiving image signals from the camera and for processingthe same. Such an image processing unit may be, inter alia, a componentof a driver assistance system or of a system for an autonomous operationof the means of transport. Moreover, this preferred specific embodimentprovides that the image processing unit be connectable by informationtechnology to the evaluation unit in accordance with the presentinvention, allowing it to transmit the below specified road wetnessinformation to the image processing unit. Alternatively or additionallyto this specific embodiment, the image processing unit may be acomponent of the evaluation unit itself (or also vice versa), allowing acommunication between these two components to take place directly andnot via the electrical system of the means of transport. This may berealized, for example, in such a way that a logic to be executed by theevaluation unit in accordance with the present invention forimplementing the method steps in accordance with the present inventionis implemented in the form of a computer program by the image processingunit.

In a third step of the example method according to the presentinvention, the road wetness information is ascertained on the basis ofthe first signal. For this purpose, the evaluation unit may compare anoise level of the first signal to a predefined threshold value for anoise level that may be stored in the memory unit connected to theevaluation unit. The predefined threshold value for a noise level ispreferably selected in such a way that when the noise level exceeds thepredefined threshold value, a current road wetness may be assumed.Conversely, when the noise level falls below the predefined thresholdvalue, a dry road surface may be assumed. A result of determining theroad wetness information may, in turn, be stored in the memory unit.Alternatively or additionally to a pure distinction between a wet or adry road surface, in the case that the noise level of the first signalexceeds the predefined threshold value, the evaluation unit may estimatea degree of wetness by taking into consideration a level of exceedanceof the predefined threshold value by the noise level of the firstsignal. Moreover, it is also possible to use a plurality of predefinedthreshold values for a noise level, the respective predefined thresholdvalues being able to correspond to different velocities and/or velocityranges of the means of transport. In other words, it may be advantageousfor the evaluation unit to receive information about a current velocityof the means of transport provided via the electrical system of themeans of transport, making it possible for the evaluation unit to selecta respectively corresponding, predefined threshold value from aplurality of predefined threshold values as a function of a value of acurrent velocity since a higher velocity is typically associated with ahigher noise level in the first signal. This makes it possible toprevent the evaluation unit from erroneously detecting a road wetness ata higher velocity of the means of transport, although the road surfaceis actually in a dry state.

In a fourth step of the example method according to the presentinvention, a predefined set of parameters is selected from a pluralityof predefined sets of parameters as a function of the road wetnessinformation. The plurality of predefined sets of parameters may, forexample, represent different configurations of a classifier which isadapted for analyzing an environment of the means of transport on thebasis of the second signal and for detecting objects in thisenvironment. Preferably, such a classifier may be part of a computerprogram that is executed by the image processing unit and/or theevaluation unit. In the event that the evaluation unit according to thepresent invention and the image processing unit are implemented asseparate components, the predefined set of parameters may be selected bythe image processing unit as a function of the road wetness informationand possibly other information (for example, as a function of a velocityof the means of transport), which the evaluation unit may provide viathe electrical system of the means of transport. An aim of usingdifferent predefined sets of parameters for the environment recognitionis using those which are adapted to a current environment (i.e., wet ordry). The reason for this is that, in the course of environmentrecognition, a classifier trained for a dry environment is generallyonly able to ensure inadequate or unreliable results in a wetenvironment, for example, due to water (tire spray) splashed up by meansof transport in front. Conversely, a classifier trained for a wetenvironment, in turn, is often not able to provide optimum recognitionresults in a dry environment. If the wetness information provided by theevaluation unit include information about a degree of wetness inaddition to a pure wetness/dryness distinction, a predefined set ofparameters adapted to the particular degree of wetness may additionallybe selected as a function thereof.

In a fifth step of the example method according to the presentinvention, an environment recognition is performed on the basis of thesecond signal in conjunction with the predefined set of parameters.Since it is possible to use predefined sets of parameters, which areadapted in each case to the environment recognition on the basis of theavailable wetness information, a performance of the environmentrecognition may be optimized accordingly. An enhanced reliability of theenvironment recognition resulting therefrom may, in turn, lead togreater certainty upon use of the means of transport.

Preferred embodiments of the present invention are described herein.

In accordance with an advantageous embodiment of the present invention,the road wetness information may additionally be ascertained as afunction of a velocity and/or an acceleration and/or a motor speed ofthe means of transport. The above, which is already described in detail,advantageously takes into account a current velocity in determiningcurrent road wetness information. Analogously thereto, values of acurrent acceleration and/or of a current motor speed of the means oftransport, which are received via the electrical system of the means oftransport, may advantageously be similarly taken into account.

In another advantageous embodiment of the present invention, thepredefined set of parameters may represent a configuration of a trained,self-learning system. This means that the classifier described above maybe realized on the basis of a self-learning system, for example, such asa neural network (for example, having a deep learning structure).Moreover, other types of self-learning systems may also be used. In thismanner, training runs of the means of transport may be conducted indifferent wetness situations and the respective trained configurationsof the self-learning system stored in the form of different predefinedsets of parameters.

In another advantageous embodiment of the present invention, thepredefined sets of parameters may be alternatively or additionallyselected as a function of a change in the noise level and/or a currenttemperature and/or an amount of water present in the environment of themeans of transport. As described above, a change in the noise level maybe caused by different amounts of water on a road surface. Moreover, achange in the noise level may also be caused, however, by a change in adistance to vehicles in front. Due to the associated, changed visibilityconditions, it may be expedient in both cases to use corresponding,adapted sets of parameters for the environment recognition. Byadditionally analyzing the second signal, it is possible to distinguishwhether a change in the noise level is caused by a changed amount ofwater or by changes in the distance of vehicles in front, for example,by ascertaining an altered size of vehicles directly in front.Alternatively or additionally, signals from other environment sensors ofthe means of transport may also be used to evaluate a current situation.It may be especially advantageous here to consider information aboutdistance to vehicles in front from a LIDAR and/or a radar system of themeans of transport. The predefined sets of parameters generated and usedfor the cases mentioned above may have the effect of making it possibleto better and/or more rapidly recognize means of transport, which arepartially concealed by a spray cloud, even if the camera is only able tocapture vague outlines of means of transport in front.

Moreover, when selecting the predefined set of parameters, it may beuseful to take into account a current outside temperature since anoutside temperature of less than 4° C. and, in particular, of less than0° C. makes it possible to infer the potential presence of snow on theshoulder and/or on the roadway itself. It may be highly probable thatsnow is present, at least on the shoulder, when there is an outsidetemperature of 0° C. or less and, at the same time, a detected roadwetness. On the basis of this information, another suitable predefinedset of parameters may be selected and used in the course of theenvironment recognition, making it possible for a road edge to bereliably recognized, for example, even when snow is present.

In another advantageous embodiment of the present invention, the roadwetness information may be ascertained as a function of a freedom frominterference of the first signal. Freedom from interference is to beunderstood here as the absence of a wide variety of interferenceeffects, which make it more difficult or even impossible to reliablydetect road wetness, such as building construction on the roadsideand/or other means of transport in the immediate vicinity of the meansof transport. Such interference effects may be determined, for example,on the basis of the second signal or on the basis of signals from otherenvironment sensors, such as LIDAR and/or radar sensors. If aninterference effect of the type under discussion is present, theevaluation unit may transmit road wetness information, which representsa road wetness condition prior to the occurrence of the interferenceeffect, to the image processing unit. The overall system may continue touse this value as road wetness information, preferably until theinterference effects have disappeared from the environment of the meansof transport. In this manner, especially time-limited interferenceeffects may also be advantageously avoided since the short-termappearance and disappearance thereof do not lead to undesirably frequentchanges in the road wetness information. This, in turn, preventsfrequently changing the predefined sets of parameters undesirably.

As described above, the first ultrasonic sensor may be mounted on themeans of transport in such a way that a detection range of the firstultrasonic sensor lies in the direction of travel of the means oftransport or counter thereto. Moreover, the environment of the means oftransport may additionally be detected on the basis of a secondultrasonic sensor and, in particular, detected by a second ultrasonicsensor, which is mounted on the means of transport in such a way that adetection range of the second ultrasonic sensor lies in the direction oftravel of the means of transport or counter thereto. In a preferredvariant, the first ultrasonic sensor, for example, may be oriented inthe direction of travel of the means of transport and the secondultrasonic sensor counter thereto. In this manner, the road wetnessinformation may be ascertained on the basis of both ultrasonic sensors,whereby an additional checking of the plausibility of the road wetnessinformation obtained from the respective first signals is possible.Alternatively, the road wetness information may be alternatelydetermined on the basis of the first or second ultrasonic sensor byevaluating the first signal of that ultrasonic sensor for road wetness,which has the lowest proportion of interference effects at a currentpoint in time. In this connection, it is noted that, in addition to thefirst and second ultrasonic sensor, other ultrasonic sensors may be usedfor the method according to the present invention. This means thatthird, fourth and so on ultrasonic sensors may be used, for example,which may be combined and used analogously to the embodiments describedabove. The first, second, third, fourth and possibly further ultrasonicsensor(s) are explicitly not limited in the placement thereof to thefront and/or rear part of the means of transport.

Another advantageous embodiment of the present invention provides thatthe plausibility of the road wetness information ascertained from thefirst signal be checked using a road wetness information ascertainedfrom the second signal. This may be accomplished by analyzingreflections of light sources in the camera image, for example, bychecking whether these light sources lie above or apparently below aroadway plane. Moreover, the plausibility of the road wetnessinformation may also be validated by other sensors and/or control unitsof the means of transport. Here, a rain sensor mounted on a windshieldof the means of transport is possible, for example, or also othersensors of the means of transport.

Information about objects in the environment of the means of transportascertained by the environment recognition may subsequently betransmitted, inter alia, to a driver assistance system and/or to asystem for autonomously controlling the means of transport and usedthere.

In accordance with a second aspect of the present invention, anapparatus is provided for supporting a camera-based environmentrecognition of a means of transport using road wetness information froma first ultrasonic sensor. In accordance with an example embodiment ofthe present invention, the apparatus includes an evaluation unit and adata input. The evaluation unit may be in the form of an ASIC, FPGA,processor, digital signal processor, microcontroller, or the like and beconnected by information technology to an internal and/or externalmemory unit. Moreover, the evaluation unit may be adapted to implementthe method according to the present invention in conjunction with acomputer program executed by the evaluation unit. Furthermore, inconjunction with the data input, the evaluation unit is adapted forrecording a first signal determined by the first ultrasonic sensor ofthe means of transport representing an environment of the means oftransport and for recording a second signal determined by a camera ofthe means of transport representing the environment of the means oftransport. The ultrasonic sensor may preferably be an already existingultrasonic sensor of the means of transport. In addition, the ultrasonicsensor may be mounted in a front bumper or in the area of a rear-endsection of the means of transport or also at other positions of themeans of transport, for example, making it possible for either theroadway ahead or behind and the environment thereof to be recorded. Thecamera may be a 2D or 3D camera, for example, having a standard imageresolution, an HD or an ultra HD image resolution, or an infraredcamera. The camera may preferably be mounted and oriented on the meansof transport in a way that enables it to record an environment ahead ofthe same. The evaluation unit may be directly and/or indirectlyconnected by information technology via an electrical system of themeans of transport to the ultrasonic sensor and the camera. Moreover,the evaluation unit is adapted for ascertaining road wetness informationon the basis of the first signal, for selecting a predefined set ofparameters from a plurality of predefined sets of parameters as afunction of the road wetness information, and for performing anenvironment recognition on the basis of the second signal in conjunctionwith the predefined set of parameters.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention are described in detailbelow with reference to the figures.

FIG. 1 shows a flow chart illustrating steps of an exemplary embodimentof a method according to the present invention.

FIG. 2 shows a block diagram of an apparatus according to the presentinvention in conjunction with a means of transport.

FIG. 3 shows a diagram of a velocity-dependent noise level of a firstultrasonic sensor.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

FIG. 1 shows a flow chart illustrating steps of an exemplary embodimentof a method according to the present invention for supporting acamera-based environment recognition of a means of transport 80 usingroad wetness information from a first ultrasonic sensor 30. In a firststep 100, an inventive evaluation unit 10, which is a microcontroller,is used for recording a first signal representing an environment 60 ofmeans of transport 80 via first ultrasonic sensor 30 of means oftransport 80. First ultrasonic sensor 30 is disposed in a front apron ofmeans of transport 80 and oriented in the direction of travel thereof.Evaluation unit 10 receives the first signal via a data input 12 thereofand stores environment information represented by the first signal in aninternal memory unit 20 of the microcontroller. In step 200, a camera 40of means of transport 80 records a second signal representingenvironment 60 of means of transport 80. Camera 40 is mounted in aninterior of means of transport 80 in an upper region of a windshieldthereof and oriented to capture an environment 60 ahead of the same. Animage processing unit of means of transport 80 that is connected byinformation technology to camera 40, receives second signal from camera40. The first signal from ultrasonic sensor 30 and the second signalfrom camera 40 are essentially acquired at an identical instant. In step300, a computer program executed by evaluation unit 10 ascertains roadwetness information on the basis of the first signal. For this purpose,evaluation unit 10 compares a noise level 70 of the first signal to apredefined threshold value 75 for a noise level 70. When noise level 70exceeds predefined threshold value 75, the presence of road wetness inenvironment 60 of means of transport 80 may be inferred. Since, in thiscase, the presence of road wetness is recognized on the basis ofpredefined threshold value 75, evaluation unit 10 transmits a signal,which is indicative thereof and contains the current road wetnessinformation, via a vehicle bus of an electrical system of means oftransport 80 to the image processing unit. In step 400 of the methodaccording to the present invention, the image-processing unit selects apredefined set of parameters from a plurality of predefined sets ofparameters as a function of the received road wetness information. Theset of parameters, which the image processing unit selects in this case,represents a configuration of a classifier based on a neural networkwhich had been trained at an earlier point in time (for example, in adevelopment phase of means of transport 80) under similar wet roadconditions. In step 500, image-processing unit performs an environmentrecognition on the basis of the second signal in conjunction with thepredefined set of parameters. Information about objects in environment60 of means of transport 80 ascertained by environment recognition isthen transmitted by the electrical system to a system for autonomouslycontrolling means of transport 80 and used by the same in the course ofautonomously controlling means of transport 80.

FIG. 2 shows a block diagram of an apparatus according to the presentinvention in conjunction with a means of transport 80. The apparatusincludes an evaluation unit 10 which, here, is a microcontroller and hasa data input 12. Evaluation unit 10 is connected by data input 12 to afirst ultrasonic sensor 30 oriented in the travel direction of means oftransport 80, and a second ultrasonic sensor 35 oriented counter to thetravel direction is connected by information technology via anelectrical system of means of transport 80. Via data input 12,evaluation unit 10 is likewise connected by information technology viathe electrical system of means of transport 80 to a camera 40 orientedin the travel direction of means of transport 80. Moreover, evaluationunit 10 is connected by information technology to an external memoryunit 20 which is adapted for storing information received by evaluationunit 10 for a subsequent processing by evaluation unit 10. With theassistance of first ultrasonic sensor 30, second ultrasonic sensor 35and camera 40, evaluation unit 10 is able to capture an environment 60of means of transport 80 at substantially identical instants. In thisexample, all steps of the example method in accordance with the presentinvention are executed in evaluation unit 10 itself, i.e., evaluationunit 10 is not only adapted for determining road wetness information onthe basis of first signals from first ultrasonic sensor 30 and secondultrasonic sensor 35, but also for selecting a predefined set ofparameters, which corresponds with the road wetness information, and forperforming an environment recognition using the predefined set ofparameters on the basis of a second signal from camera 40.

FIG. 3 shows a diagram of a velocity-dependent noise level 70 of a firstultrasonic sensor 30. In a first phase P1 of the diagram, a means oftransport 80, which uses first ultrasonic sensor 30 along the lines ofthe method according to the present invention, travels at a velocity v,which corresponds to a predefined threshold value 75 of first phase P1.In other words, because of an initially relatively low velocity v ofmeans of transport 80 in first phase P1, that predefined threshold value75 of a plurality of predefined threshold values 75, which haspreviously been set for this velocity range, is used for comparison withnoise level 70 of the first signal. Since noise level 70 in first phaseP1 is completely above predefined threshold value 75 of first phase P1,an evaluation unit 10 according to the present invention ascertains thepresence of a road wetness. From the profile of velocity v, it isdiscernible that velocity v of means of transport 80 continues toincrease here over time. Upon reaching a velocity value v1, evaluationunit 10 selects a predefined threshold value 75, which deviates frompredefined threshold value 75 of first phase P1, for a second phase P2on the basis of higher velocity v existing at this stage. Predefinedthreshold value 75 of second phase P2 is thereby adapted to noise level75 produced by higher velocity v. As in first phase P1, the presence ofa road wetness is initially detected here again since, at the beginningof second phase P2, noise level 70 is above predefined threshold value75 of second phase P2. At a point in time t1 in second phase P2, thecurve of noise level 70 drops to below predefined threshold value 75 ofsecond phase P2. In response thereto, evaluation unit 10 ascertains adry road surface.

What is claimed is:
 1. A method for supporting a camera-basedenvironment recognition by a transport device using road wetnessinformation from a first ultrasonic sensor, comprising the followingsteps: recording a first signal representing an environment of thetransport device via the first ultrasonic sensor of the transportdevice; recording a second signal representing the environment of thetransport device via a camera of the transport device; ascertaining theroad wetness information based on the first signal, wherein the roadwetness information is ascertained by comparing a noise level of thefirst signal to a velocity-dependent predefined threshold value of aplurality of predefined threshold values, wherein the plurality ofpredefined threshold values are based on a velocity range; selecting apredefined set of parameters from a plurality of predefined sets ofparameters as a function of the road wetness information; and performingan environment recognition based on the second signal in conjunctionwith the selected predefined set of parameters.
 2. The method as recitedin claim 1, wherein the first signal and the second signal are recordedat a substantially identical instant.
 3. The method as recited in claim1, wherein the road wetness information is additionally ascertained as afunction of a velocity of the transport device and/or an acceleration ofthe transport device and/or a motor speed of the transport device. 4.The method as recited in claim 1, wherein the predefined set ofparameters represent a configuration of a trained, self-learning system.5. The method as recited in claim 1, wherein the predefined set ofparameters are selected as a function of a change in the noise leveland/or a current outside temperature and/or an amount of water presentin the environment of the transport device.
 6. The method as recited inclaim 1, wherein the road wetness information is ascertained as afunction of a freedom from interference of the first signal.
 7. Themethod as recited in claim 1, wherein the first ultrasonic sensor ismounted on the transport device in such a way that a detection range ofthe first ultrasonic sensor lies in a direction of travel of thetransport device or counter to the direction of travel of the transportdevice.
 8. The method as recited in claim 1, where the environment isdetected based on a second ultrasonic sensor, which is mounted on thetransport device in such a way that a detection range of the secondultrasonic sensor lies in a direction of travel of the transport deviceor counter to the direction of travel of the transport device.
 9. Themethod as recited in claim 1, wherein plausibility of the road wetnessinformation ascertained from the first signal is checked using roadwetness information ascertained from the second signal.
 10. An apparatusfor supporting a camera-based environment recognition by a transportdevice using road wetness information from a first ultrasonic sensor,comprising: an evaluation unit; and a data input; wherein the evaluationunit is configured to, in conduction with the data input: record a firstsignal representing an environment of the transport device determined bythe first ultrasonic sensor of the transport device; record a secondsignal representing the environment of the transport device determinedby a camera of the transport device; ascertain the road wetnessinformation based on the first signal, wherein the road wetnessinformation is ascertained by comparing a noise level of the firstsignal to a velocity-dependent predefined threshold value of a pluralityof predefined threshold values, wherein the plurality of predefinedthreshold values are based on a velocity range; select a predefined setof parameters from a plurality of predefined sets of parameters as afunction of the road wetness information; and performing an environmentrecognition based on the second signal in conjunction with the selectedpredefined set of parameters.